Practice Term Frequency – Inverse Document Frequency (TF-IDF) - 9.4.2 | 9. Natural Language Processing (NLP) | Data Science Advance
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Term Frequency – Inverse Document Frequency (TF-IDF)

9.4.2 - Term Frequency – Inverse Document Frequency (TF-IDF)

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Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What does TF stand for?

💡 Hint: It's the first part of TF-IDF.

Question 2 Easy

What does IDF measure?

💡 Hint: Think of the word 'Inverse' in IDF.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does TF-IDF measure?

The frequency of a word
Word importance in a document
Document length

💡 Hint: Think about why we analyze text.

Question 2

True or False: High IDF suggests a term is common across documents.

True
False

💡 Hint: Focus on the meaning of 'Inverse'.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

You have 5 documents and the term 'machine' appears in 3. Calculate its IDF and TF given it appears 4 times in a document of 200 words.

💡 Hint: Calculate IDF, then TF, and multiply them.

Challenge 2 Hard

If a term appears in every document of a dataset and its TF is high, what does that imply about its IDF?

💡 Hint: Consider why commonality affects uniqueness.

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